CopulaCenR: Copula-Based Regression Models for Multivariate Censored Data

Copula-based regression models for multivariate censored data, including bivariate right-censored data, bivariate interval-censored data, and right/interval-censored semi-competing risks data. Currently supports Clayton, Gumbel, Frank, Joe, AMH and Copula2 copula models. For marginal models, it supports parametric (Weibull, Loglogistic, Gompertz) and semiparametric (Cox and transformation) models. Includes methods for convenient prediction and plotting. Also provides a bivariate time-to-event simulation function and an information ratio-based goodness-of-fit test for copula. Method details can be found in Sun (2019) Lifetime Data Analysis, Sun (2021) Biostatistics, Sun (2022) Statistical Methods in Medical Research, Sun (2022) Biometrics, and Sun et al. (2023+) JRSSC.

Version: 1.2.3
Depends: R (≥ 3.5.0)
Imports: boot, caret, copBasic, copula, corpcor, flexsurv, foreach, icenReg, magrittr, plotly, pracma, survival, VineCopula
Published: 2023-09-23
DOI: 10.32614/CRAN.package.CopulaCenR
Author: Tao Sun, Ying Ding
Maintainer: Tao Sun <sun.tao at>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: CopulaCenR results


Reference manual: CopulaCenR.pdf


Package source: CopulaCenR_1.2.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): CopulaCenR_1.2.3.tgz, r-oldrel (arm64): CopulaCenR_1.2.3.tgz, r-release (x86_64): CopulaCenR_1.2.3.tgz, r-oldrel (x86_64): CopulaCenR_1.2.3.tgz
Old sources: CopulaCenR archive


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